refactor(usage): extract indexing metering helper; address review round 2
Round-2 claude-review findings: - 🟡 Base-class recursion invariant: documented on embed_with_usage / embed_batch_with_usage that a provider overriding embed()/embed_batch() to delegate to the *_with_usage variant MUST also override that variant, or the two recurse. (No recursion today; the shipped providers pair the overrides.) - 🟡 Processor metering had no unit test: extracted the two-event recording into a module-level record_indexing_usage() helper and added tests/unit/test_processor_metering.py (value mapping, flag/zero-chunk no-ops, best-effort failure swallowed). - 🟡 SonarQube hotspots (python:S5332) were 3 http:// URLs in the new test fixtures (mock hosts, never contacted) blocking the quality gate (new_security_hotspots_reviewed). Switched them to https:// so no hotspot is raised. - 🟢 Zero-chunk guard: record_indexing_usage() no-ops when chunk_count == 0, so an empty document no longer writes zero-value billing rows. Deferred (stated on the PR): Mistral x.index-or-0 sort key (pre-existing, equivalent), CHANGELOG note for the Ollama /api/embed switch (CHANGELOG is commitizen-generated from commit bodies, which document it), class-var query_token_count (safe under the per-request instance pattern). Deck #67. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Opus 4.8
parent
a0bb5642cb
commit
d15ce627ab
@@ -75,6 +75,12 @@ class Provider(ABC):
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usage from their embedding response override this. Used by the
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usage from their embedding response override this. Used by the
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usage-metering hooks (Deck #67) to bill ``embeddings_queries`` by
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usage-metering hooks (Deck #67) to bill ``embeddings_queries`` by
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tokens rather than by operation count.
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tokens rather than by operation count.
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IMPORTANT (recursion invariant): this default calls ``self.embed``. A
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provider that overrides ``embed()`` to delegate to ``embed_with_usage()``
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(to avoid duplicating request logic) MUST also override this method, or
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the two will call each other forever. The shipped providers that use
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that delegation (Bedrock) do override both — keep that pairing.
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"""
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"""
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embedding = await self.embed(text)
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embedding = await self.embed(text)
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return embedding, self._estimate_tokens([text])
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return embedding, self._estimate_tokens([text])
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@@ -86,6 +92,11 @@ class Provider(ABC):
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Returns ``(embeddings, token_count)``; the default estimates. See
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Returns ``(embeddings, token_count)``; the default estimates. See
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:meth:`embed_with_usage`.
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:meth:`embed_with_usage`.
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IMPORTANT (recursion invariant): this default calls ``self.embed_batch``.
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A provider that overrides ``embed_batch()`` to delegate to
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``embed_batch_with_usage()`` (Mistral, OpenAI, Ollama do) MUST also
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override this method, or the two recurse infinitely. Keep the pairing.
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"""
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"""
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embeddings = await self.embed_batch(texts)
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embeddings = await self.embed_batch(texts)
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return embeddings, self._estimate_tokens(texts)
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return embeddings, self._estimate_tokens(texts)
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@@ -112,6 +112,65 @@ def should_use_page_aware(
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return page_aware_enabled and doc_type == "file" and bool(page_boundaries)
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return page_aware_enabled and doc_type == "file" and bool(page_boundaries)
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async def record_indexing_usage(
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*,
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enabled: bool,
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provider: str,
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model: str,
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doc_type: str,
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user_id: str,
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chunk_count: int,
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token_count: int,
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total_chars: int,
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) -> None:
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"""Record the two billable usage events for one embedded document.
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``pages_chunks`` is the volume (chunks embedded); ``embeddings_queries`` is
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the embedding request's token count — the same metric search records, so the
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meter bills embedding tokens whether they were incurred indexing a document
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or embedding a query (Deck #67).
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Best-effort and flag-gated: a metering failure is logged and never breaks
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indexing. No-op when metering is disabled or the document produced no chunks
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(an empty batch embeds nothing and would only write zero-value rows).
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Privacy note: ``user_id`` stays tenant-local — the CP rollup aggregates
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GROUP BY (day, metric) into ``usage_daily`` (no metadata column), so nothing
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here reaches Stripe; it is retained only to keep Deck #67's future per-user
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attribution derivable from the app DB without a re-migration.
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"""
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if not enabled or chunk_count == 0:
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return
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metadata = {
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"provider": provider,
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"model": model,
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"doc_type": doc_type,
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"user_id": user_id,
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"total_chars": total_chars,
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}
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try:
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store = await UsageEventStore.shared()
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# enabled=True: the guard above already confirmed the flag, so the store
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# skips a second uncached Settings build per record (ADR-024).
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await store.record_usage_event(
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metric="pages_chunks", value=chunk_count, metadata=metadata, enabled=True
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)
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await store.record_usage_event(
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metric="embeddings_queries",
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value=token_count,
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metadata=metadata,
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enabled=True,
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)
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except Exception:
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# Reached only when shared()/store construction itself raises
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# (record_usage_event swallows its own write failures). Metering is on,
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# so warn rather than hide the "enabled but no billing data" case.
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logger.warning(
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"usage metering hook (indexing embeddings) skipped", exc_info=True
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)
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async def processor_task(
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async def processor_task(
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worker_id: int,
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worker_id: int,
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receive_stream: MemoryObjectReceiveStream[DocumentTask],
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receive_stream: MemoryObjectReceiveStream[DocumentTask],
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@@ -825,54 +884,20 @@ async def _index_document(
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chunks=len(chunk_texts),
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chunks=len(chunk_texts),
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chars=total_chars,
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chars=total_chars,
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)
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)
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# Usage metering (Deck #67): record chunks embedded as a billable
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# Usage metering (Deck #67): record the chunk volume +
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# 'pages_chunks' event. Best-effort and gated on the flag so the
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# embedding-token count for this document. Best-effort and
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# off-path (OSS default) touches no storage; placed after the
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# flag-gated; placed after the embedding succeeds so it can never
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# embedding succeeds so it can never affect the indexing path.
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# affect the indexing path. See record_indexing_usage for the
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#
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# metric/privacy details.
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# Privacy note: user_id stays tenant-local — the CP rollup
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await record_indexing_usage(
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# aggregates GROUP BY (day, metric) into usage_daily (no metadata
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enabled=settings.usage_metering_enabled,
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# column), so nothing here reaches Stripe; it is retained only to
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provider=provider,
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# keep Deck #67's future per-user attribution derivable from the
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model=settings.get_embedding_model_name(),
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# app DB without a re-migration.
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doc_type=doc_task.doc_type,
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if settings.usage_metering_enabled:
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user_id=doc_task.user_id,
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# Two billable events per indexed document: 'pages_chunks' is
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chunk_count=len(chunk_texts),
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# the volume (chunks embedded); 'embeddings_queries' is the
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token_count=embed_tokens,
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# token count of the embedding request — the same metric search
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total_chars=total_chars,
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# records, so the meter bills embedding tokens whether they were
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# incurred indexing a document or embedding a query (Deck #67).
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metering_metadata = {
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"provider": provider,
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"model": settings.get_embedding_model_name(),
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"doc_type": doc_task.doc_type,
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"user_id": doc_task.user_id,
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"total_chars": total_chars,
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}
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try:
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store = await UsageEventStore.shared()
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await store.record_usage_event(
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metric="pages_chunks",
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value=len(chunk_texts),
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metadata=metering_metadata,
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# The outer guard already confirmed the flag, so pass
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# enabled=True directly — the store then skips a second
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# uncached Settings build here (ADR-024).
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enabled=True,
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)
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await store.record_usage_event(
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metric="embeddings_queries",
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value=embed_tokens,
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metadata=metering_metadata,
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enabled=True,
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)
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except Exception:
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# Reached only when shared()/store construction itself
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# raises (record_usage_event swallows its own write
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# failures). Metering is on, so warn rather than hide the
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# "enabled but no billing data" case in DEBUG logs.
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logger.warning(
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"usage metering hook (indexing embeddings) skipped",
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exc_info=True,
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)
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)
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async def generate_sparse_embeddings():
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async def generate_sparse_embeddings():
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@@ -331,8 +331,9 @@ def test_trailing_slash_base_url_normalized():
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async def test_gateway_embed_with_usage_forwards_after_bearer(monkeypatch):
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async def test_gateway_embed_with_usage_forwards_after_bearer(monkeypatch):
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"""embed_with_usage refreshes the bearer, then returns the (embedding,
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"""embed_with_usage refreshes the bearer, then returns the (embedding,
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token_count) from the inherited OpenAI implementation."""
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token_count) from the inherited OpenAI implementation."""
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# https mock host (never contacted — the OpenAI client is patched below).
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provider = GatewayProvider(
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provider = GatewayProvider(
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base_url="http://gw:8083/v1", embedding_model="mistral/mistral-embed"
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base_url="https://gw:8083/v1", embedding_model="mistral/mistral-embed"
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)
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)
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order: list[str] = []
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order: list[str] = []
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@@ -364,8 +365,9 @@ async def test_gateway_embed_with_usage_forwards_after_bearer(monkeypatch):
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async def test_gateway_embed_batch_with_usage_forwards_after_bearer(monkeypatch):
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async def test_gateway_embed_batch_with_usage_forwards_after_bearer(monkeypatch):
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"""embed_batch_with_usage also refreshes the bearer before delegating."""
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"""embed_batch_with_usage also refreshes the bearer before delegating."""
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# https mock host (never contacted — the OpenAI client is patched below).
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provider = GatewayProvider(
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provider = GatewayProvider(
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base_url="http://gw:8083/v1", embedding_model="mistral/mistral-embed"
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base_url="https://gw:8083/v1", embedding_model="mistral/mistral-embed"
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)
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)
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ensured = {"n": 0}
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ensured = {"n": 0}
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@@ -15,8 +15,9 @@ from nextcloud_mcp_server.providers.ollama import OllamaProvider
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@pytest.fixture
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@pytest.fixture
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def ollama_provider():
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def ollama_provider():
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# Construct with no models so __init__ skips _check_model_is_loaded (no
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# Construct with no models so __init__ skips _check_model_is_loaded (no
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# network call), then enable embeddings post-construction.
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# network call), then enable embeddings post-construction. https mock host
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provider = OllamaProvider(base_url="http://ollama:11434")
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# (never contacted — client.post is patched in each test).
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provider = OllamaProvider(base_url="https://ollama:11434")
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provider.embedding_model = "nomic-embed-text"
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provider.embedding_model = "nomic-embed-text"
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return provider
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return provider
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@@ -0,0 +1,104 @@
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"""Unit tests for the indexing-path usage-metering helper (Deck #67).
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``record_indexing_usage`` records the two billable events (``pages_chunks`` +
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``embeddings_queries``) after a document's chunks are embedded. These cover the
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value mapping, the flag/zero-chunk no-ops, and the best-effort failure path
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without standing up the full document pipeline.
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"""
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from nextcloud_mcp_server.vector import processor
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@pytest.fixture
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def store_spy(monkeypatch):
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"""Patch UsageEventStore.shared() to return a spy store."""
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store = MagicMock()
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store.record_usage_event = AsyncMock()
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monkeypatch.setattr(
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processor.UsageEventStore, "shared", AsyncMock(return_value=store)
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)
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return store
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@pytest.mark.unit
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async def test_records_pages_chunks_and_token_count(store_spy):
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"""Both events fire: pages_chunks = chunk count, embeddings_queries = tokens."""
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await processor.record_indexing_usage(
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enabled=True,
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provider="mistral",
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model="mistral-embed",
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doc_type="file",
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user_id="alice",
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chunk_count=110,
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token_count=4242,
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total_chars=170826,
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)
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calls = store_spy.record_usage_event.await_args_list
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by_metric = {c.kwargs["metric"]: c.kwargs["value"] for c in calls}
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assert by_metric == {"pages_chunks": 110, "embeddings_queries": 4242}
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for c in calls:
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# Hot-path fast-gate + tenant-local attribution metadata.
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assert c.kwargs["enabled"] is True
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assert c.kwargs["metadata"]["provider"] == "mistral"
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assert c.kwargs["metadata"]["model"] == "mistral-embed"
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assert c.kwargs["metadata"]["user_id"] == "alice"
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assert c.kwargs["metadata"]["doc_type"] == "file"
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@pytest.mark.unit
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async def test_disabled_is_noop(store_spy):
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"""Flag off → no store access, no events."""
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await processor.record_indexing_usage(
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enabled=False,
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provider="mistral",
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model="mistral-embed",
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doc_type="file",
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user_id="alice",
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chunk_count=10,
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token_count=20,
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total_chars=5,
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)
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store_spy.record_usage_event.assert_not_awaited()
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@pytest.mark.unit
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async def test_zero_chunks_is_noop(store_spy):
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"""A document with no chunks records nothing (no zero-value rows)."""
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await processor.record_indexing_usage(
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enabled=True,
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provider="mistral",
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model="mistral-embed",
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doc_type="file",
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user_id="alice",
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chunk_count=0,
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token_count=0,
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total_chars=0,
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)
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store_spy.record_usage_event.assert_not_awaited()
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@pytest.mark.unit
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async def test_store_failure_is_swallowed(monkeypatch):
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"""A store-construction failure is logged, never raised into indexing."""
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monkeypatch.setattr(
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processor.UsageEventStore,
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"shared",
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AsyncMock(side_effect=RuntimeError("boom")),
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)
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# Must not raise.
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await processor.record_indexing_usage(
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enabled=True,
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provider="mistral",
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model="mistral-embed",
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doc_type="file",
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user_id="alice",
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chunk_count=3,
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token_count=7,
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total_chars=9,
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)
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Reference in New Issue
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